suppressPackageStartupMessages(library(dplyr))
suppressPackageStartupMessages(library(tidyr))
suppressPackageStartupMessages(library(magrittr))
suppressPackageStartupMessages(library(googleVis))
## Warning: package 'googleVis' was built under R version 3.3.2
## Creating a generic function for 'toJSON' from package 'jsonlite' in package 'googleVis'
suppressPackageStartupMessages(library(ggmap))
## Warning: package 'ggmap' was built under R version 3.3.2
## Warning: package 'ggplot2' was built under R version 3.3.2
suppressPackageStartupMessages(library(leaflet))
## Warning: package 'leaflet' was built under R version 3.3.2
suppressPackageStartupMessages(library(ggplot2))
suppressPackageStartupMessages(library(maps))
## Warning: package 'maps' was built under R version 3.3.2
suppressPackageStartupMessages(library(htmlwidgets))
suppressPackageStartupMessages(library(rcdimple))

schools = read.csv("JesuitColleges.csv")
selectschools <- select(schools, c(1,2,3,4,8,10))
locationschools1 <- select(selectschools, c(5,6))

locationschools <- unite(locationschools1, City_Country, City, Country, sep = ", ", remove=TRUE)

Establishment of Jesuit Institutions

suppressPackageStartupMessages(library(dplyr))
library(DT)
## Warning: package 'DT' was built under R version 3.3.2
dt=datatable(selectschools, options=list(pageLength = 10))
dt

The table above shows a list of Jesuit higher education institutions. One can sort the information by region, name of the institution, institution website, the year the insitution was founded, and its location by city or country.

Based on the table, the first two Jesuit institutions established were both from the European Union in Rome, Italy founded in 1551 and London, England in the United Kingdom founded in 1614. Within a decade, another insitution was founded in Bogota, Columbia in Latin America, but it was not until after the 1930s that more Jesuit institutions arose in that region. Instutitions began to appear in the 19th century for both the South Asian and North American regions. The Asian Pacific and African Jesuit instituions were not established until the 20th century. The African region was the last to establish any Jesuit institutions with its first institution being established in 1954.

whatislatlon=function(mydata,addressindata){
locs=geocode(as.character(unique(mydata[,addressindata])))
locs$address=unique(mydata[,addressindata])
mydata$latitude=locs$lat[ match(mydata[,addressindata],locs$address)]
mydata$longitude=locs$lon[ match(mydata[,addressindata],locs$address)]
return(mydata)
}

Location/Spread of Jesuit Institutions of Higher Education

The map below displays the locations of Jesuit institutions of higher education.

suppressMessages(library(ggplot2))
suppressMessages(library(ggmap))

location = whatislatlon(locationschools, "City_Country")
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Harare,%20Zimbabwe&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Abidjan,%20Ivory%20Coast&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Monze,%20Zambia&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Bevalala,%20Madagascar&sensor=false
## Warning: geocode failed with status ZERO_RESULTS, location = "Bevalala,
## Madagascar"
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Antananarivo,%20Madagascar&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Nairobi,%20Kenya&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Kinshasa,%20Congo&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Abidjan%2027,%20Ivory%20Coast&sensor=false
## Warning: geocode failed with status ZERO_RESULTS, location = "Abidjan 27,
## Ivory Coast"
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Johannesburg,%20South%20Africa&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Lusaka,%20Zambia&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Yaounde,%20Cameroon&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Davao%20City,%20Philippines&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Quenzon%20City,%20Philippines&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Naga%20City,%20Philippines&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Zamboanga%20City,%20Philippines&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Rawasari%20Jakarta,%20Indonesia&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Hiroshima,%20Japan&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Taipei,%20Taiwan&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Parkville,%20Austrailia&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Surakarta,%20Indonesia&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Culion,%20Philippines&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Quezon%20City,%20Philippines&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Hong%20Kong,%20China&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Yogyakarta,%20Indonesia&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Seoul,%20Republic%20of%20Korea&sensor=false
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## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Cagayan%20de%20Oro,%20Philippines&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Oxford,%20United%20Kingdom&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Paris,%20France&sensor=false
## .
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## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Barcelona,%20Spain&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Seville,%20Spain&sensor=false
## .
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## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Zagreb,%20Croatia&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=London,%20United%20Kingdom&sensor=false
## .
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Dublin,%20Ireland&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Uppsala,%20Sweden&sensor=false
## .
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Cagilari,%20Italy&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Moscow,%20Russian%20Federation&sensor=false
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## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Madrid,%20Spain&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Bibao,%20Spain&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Beirut,%20Lebanon&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Namur,%20Belgium&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Krakow,%20Poland&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Sao%20Bernardo%20do%20Campo,%20Brazil&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Belo%20Horizonte,%20Brazil&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=San%20Miguel,%20Argentina&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=San%20Crist%F3bal,%20Dominican%20Republic&sensor=false
## Warning in readLines(connect, warn = FALSE): cannot open URL 'http://
## maps.googleapis.com/maps/api/geocode/json?address=San%20Crist%F3bal,
## %20Dominican%20Republic&sensor=false': HTTP status was '400 Bad Request'
## Warning in FUN(X[[i]], ...):   geocoding failed for "San Cristóbal, Dominican Republic".
##   if accompanied by 500 Internal Server Error with using dsk, try google.
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Santo%20Domingo,%20Dominican%20Republic&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Oaxaca,%20Mexico&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Asuncion,%20Paraguay&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Tlaquepaque,%20Mexico&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Caracas,%20Venezuela&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Rio%20de%20Janeiro,%20Brazil&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Quito,%20Ecuador&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Cali,%20Colombia&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Bogota,%20Colombia&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Santiago,%20Chile&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Lima,%20Peru&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Cordoba,%20Argentina&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Recife,%20Brazil&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=San%20Cristobal,%20Venezuela&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Montevideo,%20Uruguay&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Managua,%20Nicaragua&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=San%20Salvador,%20El%20Salvador&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Mexico,%20Mexico&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Tijuana,%20Mexico&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Torreon,%20Mexico&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Leon,%20Mexico&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Puebla,%20Mexico&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Acapulco,%20Mexico&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Guatemala%20City,%20Guatemala&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Sao%20Leopoldo,%20Brazil&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Chestnut%20Hill,%20United%20States%20of%20America&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Regina,%20Canada&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Buffalo,%20United%20States%20of%20America&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Worcester,%20United%20States%20of%20America&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Omaha,%20United%20States%20of%20America&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Fairfield,%20United%20States%20of%20America&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Bronx,%20United%20States%20of%20America&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Washington,%20United%20States%20of%20America&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Spokane,%20United%20States%20of%20America&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Cleveland,%20United%20States%20of%20America&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Syracuse,%20United%20States%20of%20America&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Los%20Angeles,%20United%20States%20of%20America&sensor=false
## .
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## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Toronto,%20Canada&sensor=false
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## .
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## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Philadelphia,%20United%20States%20of%20America&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=St.%20Louis,%20United%20States%20of%20America&sensor=false
## .
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Seattle,%20United%20States%20of%20America&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Mobile,%20United%20States%20of%20America&sensor=false
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## .
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Wheeling,%20United%20States%20of%20America&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Cincinnati,%20United%20States%20of%20America&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Vijayawada,%20India&sensor=false
## .
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## .
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=East%20Garo%20Hills,%20India&sensor=false
## .
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Chennai,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Jamshedpur,%20India&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Karimnagar,%20India&sensor=false
## .
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Thiruvananthapuram,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Pulivendla,%20ndia&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Jaipur,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Tirunelveli,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Jalpaiguri%20District,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Kolkata,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Ambikapur,%20India&sensor=false
## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Palayamkottai,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Porvorim%20Alto,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Delhi,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Jabalpur,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Alto-Porvorim,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Bhubaneswar,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Mumbai%20400%20001,%20India&sensor=false
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## Information from URL : http://maps.googleapis.com/maps/api/geocode/json?address=Gamharia,%20India&sensor=false
location = location %>% group_by(City_Country,longitude,latitude) %>% summarise(Count=n()) %>% arrange(desc(Count))

library(leaflet)

leaflet() %>% addTiles() %>% addCircleMarkers(data=location, radius=~Count)
## Assuming 'longitude' and 'latitude' are longitude and latitude, respectively

The map above displays the global spread of Jesuit institutions for higher education. Excluding any other relatively relevant information, we can notice the disperse and clustering of universities and colleges over the globe. Ethnic and religious tendencies of specific regions are likely the cause of the clustering of higher education institutions, though the opportunity to create and develop universities is also necessary.

Student-to-faculty Ratio

suppressPackageStartupMessages(library(rcdimple))

ratioschools <- select(schools, c(1,12,13,14)) %>% group_by(Region, add = FALSE) %>% na.omit()
ratioschools = ratioschools[,c(1,2,4,3)]
ratioschools = ratioschools %>% group_by(Region) %>% summarise_each(funs(sum),Alumni,Undergraduate.Enrollment,Staff) 

ratioschool <- ratioschools %>% gather(Type,Population,3,4) %>% group_by(Region) %>% arrange(desc(Population))


dimple(
  Region ~ Population,
  groups = "Type",
  data = ratioschool,
  type = "bar"
) %>%
  xAxis(type = "addMeasureAxis") %>%
  yAxis(type = "addCategoryAxis", orderRule = desc("Population")) %>%
  add_legend(
    x = 200,
    y = 10,
    width = 400,
    height = 40,
    horizontalAlign = "right") %>%
  add_title(text= "Student-to-Faculty Ratio")
ratiosum = ratioschools %>% mutate(Ratio= Undergraduate.Enrollment/Staff) %>% arrange(desc(Ratio))
ratiosum = ratiosum[,c(1,3,4,5,2)]
ratiosum$Ratio = round(ratiosum$Ratio, digits = 2)
rt=datatable(ratiosum, options=list(pageLength = 6))
rt

The graph and table above show the student-to-faculty ratio of Jesuit higher education institutions by Region. Africa has the smallest undergraduate population of 341 students and the smallest student-to-facutly ratio at about 3 students per faculty member while Asia Pacific has an an undergraduate population of 35,108 students with the largest student-to-faculty ratio at about 13 students per faculty member. In comparison to Latin America which has the largest undergraduate population at 1276,795 students and a ratio of about 6 students per faculty member, the Asian Pacific region does not have a good student-to-faculty ratio in terms of one-on-one attention for students.

A Look at Faculty-to-Student Ratio

The scatterplot below was created to see if there was any correlation or trend between the student-to-faculty ratio and the amount of alumni each region has.

ratiosum$Alumni = as.character(ratiosum$Alumni)
ratiosum$Alumni = as.numeric(ratiosum$Alumni)
ratiooutcome = select(ratiosum, c(1,4,5))

library(plotly)
## Warning: package 'plotly' was built under R version 3.3.2
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggmap':
## 
##     wind
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
outcome=ggplot(ratiooutcome,aes(x=Ratio,y=Alumni,color=Region))+geom_point()
ggplotly(outcome)
outcome

Naturally, the institutions with a higher faculty-to-student ratio have a greater alumni base. Generally, an institution boasting a minimal faculty-to-student ratio will also have a very small undergraduate class size. In turn, schools with a higher ratio will have a higher undergraduate class size. This means that as a general rule the schools with a higher faculty-to-student ratio will also have a higher undergraduate size, and they will also have a greater amount of alumni.

Staff and Total Undergraduate Enrollment

d3 <- select(schools, c(1,13,14))

library(plotly)

myggplot=ggplot(d3,aes(x=Staff,y=Undergraduate.Enrollment,color=Region))+geom_point()

ggplotly(myggplot)
myggplot
## Warning: Removed 20 rows containing missing values (geom_point).

Above, we analyze the size of undergraduate enrollment independently of faculty-to-student ratio. As expected, the total enrollment of schools is directly reflective of the staff available at a university. Of course, most institutions limit some sort of cap to their incoming freshman classes. We may also notice here, that generally universities from regions like Latin America, North America, and the Asia Pacific are substantially larger than others around the globe. Traditionally, Jesuit institutions remain smaller, private, and exclusive. However, some schools studied and listed here oppose that tradition.

Current Undergraduate Enrollment Trend

library(scatterD3)

scatter = select(schools, c(1,4,13,14))
scatter = scatter %>% na.omit()
scattermatplot=scatterD3(
   data = scatter, x=Founded,y=Undergraduate.Enrollment,col_var=Region)
scattermatplot

General School Reach & University List

Again, we may look at the spread of Jesuit institutions across the globe. Here, each highlighted country represents a country where in a Jesuit institution operates. The Jesuit-catholic ideology of educating the entire person has spread, obviously, to all corners of the world. It is recognizable and commendable that this religiously affiliated education has transcended cultures and barriers to reach as many individuals as it has. This also says something of the value of a Jesuit education: it is valued above many others, and it is valued almost everywhere. Students graduating from Gonzaga University should recognize the global community of scholars that they are inherently a part of. This unique distinction, Jesuit education, is something to be esteemed and something to be rewarded.

suppressPackageStartupMessages(library(googleVis))
G <- gvisGeoChart(selectschools, "Country", 
                  options=list(width=400, height=300))
T <- gvisTable(selectschools, 
               options=list(width=400, height=300))

GT <- gvisMerge(G,T, horizontal=TRUE) 
GT
MergedID2f6023cf7f96

Data: various • Chart ID: MergedID2f6023cf7f96googleVis-0.6.1
R version 3.3.1 (2016-06-21) • Google Terms of Use • Data Policy: See individual charts